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library_name: keras-hub
---
### Model Overview
## Example Usage
```python
import keras
import numpy as np
import requests
from PIL import Image
from keras_hub.src.models.depth_anything.depth_anything_depth_estimator import (
DepthAnythingDepthEstimator,
)
image = Image.open(requests.get("http://images.cocodataset.org/val2017/000000039769.jpg", stream=True).raw)
image = image.resize((518, 518))
depth_estimator = DepthAnythingDepthEstimator.from_preset(
"depth_anything_v2_base,
depth_estimation_type="relative",
max_depth=None,
)
images = np.expand_dims(np.array(image).astype("float32"), axis=0)
outputs = depth_estimator.predict({"images": images})["depths"]
depth = keras.ops.nn.relu(outputs[0, ..., 0])
depth = (depth - keras.ops.min(depth)) / (
keras.ops.max(depth) - keras.ops.min(depth)
)
depth = keras.ops.convert_to_numpy(depth) * 255
Image.fromarray(depth.astype("uint8")).save("depth_map.png")
```
## Example Usage with Hugging Face URI
```python
import keras
import numpy as np
import requests
from PIL import Image
from keras_hub.src.models.depth_anything.depth_anything_depth_estimator import (
DepthAnythingDepthEstimator,
)
image = Image.open(requests.get("http://images.cocodataset.org/val2017/000000039769.jpg", stream=True).raw)
image = image.resize((518, 518))
depth_estimator = DepthAnythingDepthEstimator.from_preset(
"depth_anything_v2_base,
depth_estimation_type="relative",
max_depth=None,
)
images = np.expand_dims(np.array(image).astype("float32"), axis=0)
outputs = depth_estimator.predict({"images": images})["depths"]
depth = keras.ops.nn.relu(outputs[0, ..., 0])
depth = (depth - keras.ops.min(depth)) / (
keras.ops.max(depth) - keras.ops.min(depth)
)
depth = keras.ops.convert_to_numpy(depth) * 255
Image.fromarray(depth.astype("uint8")).save("depth_map.png")
```
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